A method for calculating and retrieving building rooftop photovoltaic potential based on knowledge graphs

In the context of global efforts to transform energy structures and address climate change, accurate and prompt assessment of building rooftop photovoltaic (PV) potential plays a crucial role in sustainable urban energy planning. However, existing calculation methods face challenges adapting to the dynamic changes in urban environments and efficiently retrieving calculation results. This study presents an integrated framework for building rooftop PV potential calculation and retrieval based on knowledge graphs, incorporating a spatiotemporal ontology model, data foundation, and semantic PV potential calculation and retrieval models. Taking Suzhou City in Jiangsu Province, China, as an example, we employed the framework to calculate the building PV potential and retrieve results across multiple spatial scales. The results demonstrate the effectiveness of the framework and highlight its advantages in result retrieval, enabling flexible searches from administrative regions to any region of interest within a matter of minutes. Furthermore, we verified the adaptability and scalability of the framework in different urban environments by taking two regions, Xinjiang Uygur Autonomous Region and Hainan Province, as examples. This study provides a decision-making tool that combines spatiotemporal precision with timeliness for assessing and planning the building PV potential, facilitating differentiated PV deployment strategies, and promoting coordinated development of PV resources and zero-carbon cities.